New Brain-Like Chip Uses Light to Go Blazingly Fast

Deep learning is having a serious moment right now in the world of AI. Loosely based on the brain's computing architecture, artificial neural networks have vastly outperformed their predecessors in a variety of tasks that had previously stumped our silicon-minded comrades. But as these algorithms continuously forge new grounds in machine intelligence, we're coming to an uncomfortable realization: transistor-based computers have hard limits, and those limits are approaching rapidly. Now, thanks to a new system developed by Princeton engineers, we may have one way to smash the speed barrier of our current processors: neuromorphic computing running on photons, not electrons, with silicon chips that work at the speed of light. Published this week on Arxiv, the new photonic neural network is so blazingly efficient that when pitted against a conventional CPU in solving differential equations, it performed roughly 2,000 times faster.